We build evidence-grounded Q&A, verify every citation, and extract structured fields from contracts, filings, and clinical records — returned in your schema, with a QA gate on every batch.
Pre-screened for education, domain experience, and accuracy
Work in your annotation platform, document pipeline, or custom tooling
Real experience in finance, legal, healthcare, insurance, and more
One programme, run end to end, annotating training data, validates model outputs, and handles the complex documents your AI needs to understand.
Our delivery team operate inside your annotation platform, document pipeline, or custom tooling. You control access. Your data stays where it is.
Pay our annotation team in any country from a single dashboard. You set the rates, we add a small fixed fee on top. No hidden costs, no chasing invoices.
Every batch is reviewed before it reaches you. You get a shortlist of qualified our delivery team ready to start working in your tools. What we deliver:
Scope a project, commission qualified our delivery team, and manage everything from one platform. Your documents and tools stay exactly where they are.
Describe your document types, annotation schema, and domain requirements. Receive proposals from our delivery team who have already been screened for relevant expertise.
We agree the spec, then run delivery inside your annotation platform or document pipeline.
Share guidelines, message your team, and handle global payments from a single dashboard.
Send us a sample batch and we will come back with a spec and a quote.
A standing programme, run end to end, for continuous or large-volume work.
Send us your first batch and get managed our delivery team who have the domain expertise your project requires.
Specialists across dozens of professional domains, ready to annotate the documents your models need to understand.
Common questions about delivery our delivery team to annotate documents for AI training and evaluation.
Every batch is sampled and scored against the rubric agreed at kickoff, with a second reviewer on anything ambiguous and independent adjudication where reviewers disagree. You get the inter-rater agreement figure with each delivery, so document annotation quality is a number you can track rather than a claim we make.
The full range for document annotation: we scope the task types with you at kickoff, produce them against your schema, and QA every batch before it reaches you. If a task type is unusual, we pilot it on a small batch first so you can judge the output before committing volume.
Contracts, invoices, filings, clinical notes, policy documents, and scanned records — including poor-quality scans and mixed-language documents, which is where most extraction pipelines actually break.
We work inside whatever you already run — Label Studio, CVAT, V7, Argilla, Prodigy, or your own internal tooling. You control access and permissions, your data stays where it is, and the document annotation output lands in your system rather than ours.
Document annotation is priced per delivered unit against an agreed quality bar, or as a fixed monthly fee for a standing programme. You get the full number in writing before work starts, and you are not billed for batches that fail QA.
A managed programme means we run the whole document annotation pipeline end to end — staffing, tooling, QA, and reporting — inside your environment. It is the right choice once volume is continuous or the work spans several teams, because you stop coordinating batches and start receiving them.
Deliver our delivery team on ReinforcedX, then invite them to any third-party platform or your own custom tooling.
Three ways to work with us, from a single batch to a standing programme.
Send us the spec and we scope the work, agree the quality bar, and start delivering. We run inside the tools you already use, so output lands where your team works.
We staff, run, and QA the whole programme inside your tools. End-to-end operations for large or complex projects.
Keep a standing delivery pipeline running against your roadmap, with quality reported every week.
Typically within a week or two of a scope being agreed. The first delivery is deliberately a small batch so you can check the output against your expectations before volume ramps.
One process owner who knows the workflow, one engineer with access to the systems involved, and a weekly 45-minute review. No standing committee, and no requirement for an ML specialist on your side.
You do. Datasets, labels, weights, evaluation suites and runbooks are yours and are handed over at the end. Your data trains your models only, with zero-retention provider settings by default.
Yes, and the quality bar holds because the rubric and gold set are already agreed by that point. Ramping is a staffing question, not a re-scoping one, so it usually takes days rather than a new engagement.
Often you should not. The cases where teams move to us are when they cannot get a quality number out of their current vendor, or when the work is delivered as an opaque batch with no trace of how disagreements were resolved.
We stay on-call for 30 days at no extra cost, then move to an optional support retainer. Most teams also keep a quarterly evaluation review with us to catch drift early.
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